local
Geo de borda do visitante (cidade/UF).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Geo de borda do visitante (cidade/UF).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states that city/state information for the visitor is returned, but does not clarify the meaning of 'borda', whether this is a safe read operation, or any other behavioral constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short and contains no filler words, which is a form of conciseness. However, it is so terse that key context such as 'borda' is left undefined, so brevity comes at the cost of clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool, the description at least names the expected output domain (city/UF), but without an output schema, annotations, or explanation of 'borda', the agent still lacks important context about what this tool actually returns and how it behaves.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the schema is empty, so there are no parameter semantics to explain. The baseline of 4 for a zero-parameter tool is appropriate because this dimension is trivially satisfied.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies the resource and output fields ('visitor' and 'city/UF'), which prevents a pure tautology from the tool name 'local'. However, it lacks an explicit verb and the term 'borda' is ambiguous, leaving the tool's exact purpose unclear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to use this tool versus its siblings such as search, ia_filters, or get_cnpj. An agent would have to infer that this is a geolocation lookup from the name and the 'cidade/UF' reference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a clearly distinct purpose: exact CNPJ lookup, company search, autocomplete, AI filter generation, idea evaluation, reference data, session/watches management, and API utility endpoints. There is no meaningful overlap that would cause an agent to select the wrong tool.
The naming is inconsistent: some tools use verb_noun snake_case (get_cnpj, add_watch, list_watches), some are bare English verbs (search, suggest, contact), and some are bare nouns or abbreviations (health, local, ref, api_index). It also mixes languages, with Portuguese avaliar alongside English names.
13 tools is within a reasonable range for a server covering CNPJ lookup, search, evaluation, monitoring, and API metadata. The count feels slightly broad because several utility endpoints (health, api_index, contact, local) are auxiliary, but no tool is redundant.
The core lookup, search, evaluation, and reference workflows are covered well. However, the monitoring lifecycle is incomplete: add_watch and list_watches exist but there is no remove_watch, and monitor_session has no session status or termination counterpart, creating a dead end for the watch flow.